Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/46358

TítuloAn assessment of environmental and toxicological risk to pesticide exposure based on a case-based approach to computing
Autor(es)Coelho, Cristina
Vicente, Henrique
Martins, M. Rosário
Lima, Nelson
Neves, Mariana
Neves, José
Data2017
EditoraIOP Publishing
RevistaIOP Conference Series: Earth and Environmental Science
CitaçãoCoelho, Cristina; Vicente, Henrique; Martins, M. Rosário; Lima, Nelson; Neves, Mariana; Neves, José, An assessment of environmental and toxicological risk to pesticide exposure based on a case-based approach to computing. IOP Conference Series: Earth and Environmental Science, 52(012091), 1-11, 2017
Resumo(s)Pesticide environmental fate and toxicity depends on its physical and chemical features, the soil composition, soil adsorption, as well as residues that may be found in different soil slots. Indeed, pesticide degradation in soil may be influenced by either biotic or abiotic factors. In addition, the toxicity of pesticides for living organisms depends on their adsorption, distribution, biotransformation, dissemination of metabolites together with interaction with cellular macromolecules and excretion. Biotransformation may result in the formation of less toxic and/or more toxic metabolites, while other processes determine the balance between toxic and a nontoxic upcoming. Aggregate exposure and risk assessment involve multiple pathways and routes, including the potential for pesticide residues in food and drinking water, in addition to residues from pesticide use in residential and non-occupational environments. Therefore, this work will focus on the development of a decision support system to assess the environmental and toxicological risk to pesticide exposure, built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based attitude to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/46358
DOI10.1088/1755-1315/52/1/012091
ISSN1755-1315
e-ISSN1755-1307
Versão da editorahttp://iopscience.iop.org/journal/1755-1315
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals
CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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